🧵 of 🧵's I found useful to understand B.1.1.529 (Nu) today. From actual subject matter experts or data journalists.

1/5
Tulio de Oliveira, the director of the Centre for Epidemic Response and Innovation in South Africa.

On the rapidly changing situation in SA and sequencing.

2/5

Jeffrey Barrett lead of Covid-19 genomics initiative @sangerinstitute

On the multitude of molecular effects of genomic sequence changes.

3/5

The Bloom lab, who study viral evolution.

On potential effects for various antibody binding targets from the mutations.

4/5

the @FTs brilliant data journalist John Burn-Murdoch, who always manages to distil the most important facts and trends.

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More from @DevanSinha

25 Nov
The most robust data for vax effectiveness waning is from randomised control trials. Pfizer👇

2doses holds up well- but still complete the course and boost!

This is real world data. Prospective randomisation only reduces confounding we face in retrospective observations.

1/
Sources of bias/confounding in observational data (eg UKHSA case control study below):

▪️ accrued natural immunity in control (>45% 🏴󠁧󠁢󠁥󠁮󠁧󠁿 infected) & only a fraction tested
▪️ difficulty of retrospective matching/case controlling (high clinical risk vaxxed first, not just age)

2/
▪️ break throughs disproportionately sample higher risk (immunocompromised, preexisting conditions, etc)
▪️ lower test seeking behaviour in unvaxxed
▪️ pop highest risk of infection (urban, young, ethic minority, high deprivation) also lower vax uptake

3/
Read 9 tweets
21 Oct
The Pfizer booster trial is pretty spectacular.

10k previously 2x dosed (median 11 months from dose 2).

Randomised 1:1 placebo and 30ug.

95.6% relative risk reduction in symptomatic infection in intervention arm vs control (2dose only).

5 v 109 events 7+ days from boost.
To repeat: 95.6% RR reduction in symptomatic infection was for 3 vs 2 DOSES

UK data has 2dose Pfizer at ~80% VE vs symptomatic infection in Delta era. But follow up time <11 months in Pfizer trial.

If boost anywhere near 90% RR⬇️ we're looking at ~98% VE vs immunonaive.
They found no statistical difference for age, sex, race, ethnicity, or co-morbidities within the limitation of study size.

The primary course in the trial would have been with a 3-4 week dose interval between dose1 and dose2. (cf 10 week typical in UK).

pfizer.com/news/press-rel…
Read 4 tweets
9 Aug
80% [78,82] of England's Total population have now been vaccinated or infected

Wall of immunity:

10% Infected only
19% Both infxn+vax
51% Vaccinated 1or2 doses

Usual caveats: time lag after vax, not 100% protective, assumes random vaxing probability of previously infected etc
Remaining 11.5m unexposed/unvaxxed susceptible population is heavily skewed to younger age groups.

80% under 25yo
47% in school age kids 5-14yo

Outbreaks and cases will expectedly be concentrated in these groups now and increasingly <15 after current vax roll out plan completed
Quick check of the model against ONS serosurvey and PHE blood donor antibody surveillance, in 16yo+:

Model 95.8% (up to 8 August)
ONS 93.6% (12 - 19 July)
PHE 96.2% (28 June - 23 July)

Looks okay.
Read 7 tweets
26 May
70% [68,72] of England's Total population have now been infected or vaccinated.

Wall of immunity:

13% Infected
44% Vaccinated 1+
13% Both

Usual caveats: time lag after vax, not 100% protective, assumes random vaxxing probability of previously infected etc.

1/
Estimated numbers of people:

7.0m Infected only
24.7m Vaccinated only
7.5m Infected & vaccinated

17.1m unexposed and susceptible

2/
The remaining 17.1m unexposed/susceptible population is heavily skewed to younger age groups.

2/3 under 25
1/3 in school age kids 5-14yo

Outbreaks and cases will expectedly be concentrated in these groups now and increasingly <18 after current vax roll out plan completed.

3/
Read 5 tweets
23 May
Grateful for the hard work of dedicated public health scientists at @PHE_uk like @kallmemeg and unsung others who work overtime to produce excellent reports on the variant of concern B1.617.2 🇮🇳

🧵analysis of vax effectiveness, and why interpretation of reduced VE limited.

1/
PHE did a 'test negative case control study' w/ logistic regression as I outlined yday.

From test and vax databases they retrospectively created a control cohort of 99k who tested negative and compared to 6.4k test positive for B117 & 1k for B1.617.2

2/

PHE found a statistically significant dip in symptomatic protection after 1 vax dose.

51% ➡️ 33% against B1.617.2 variant (yellow).
For both Pfizer and Ox/AZ (21 days after 1st dose).

No statistically significant change after 2 vax doses (14 days after 2nd dose).

3/
Read 21 tweets
22 May
This is good news.

The longer it takes to statistically tell difference between vax effectiveness against variants the smaller the actual dip (if any) in protection will be.

1/
In randomised control trials we can be confident in vax effect after only 100+ infections because selection bias and confounding variables between the vaxxed and unvaxxed comparison populations are (e)limited by the randomisation process.

2/
This is not the case when we do retrospective observational studies - like vax effectiveness against variants in the field.

The statistical analysis is more challenging. There are biases in who is vaxxed or infected, living, working, mixing patterns, medical health/immunity.

3/
Read 7 tweets

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